Summary - ARMA Basics
This summary provides the basis for the ARMA models. It contains an explanation of the autocorrelation, White Noise, Partial Autocorrelation, Moving Average Model, Stationarity of the time series, weakly stationary, covariance stationary, model selection criteria, and how to interpret the graphs. This summary helps you go through material without watching again the lengthy web-lectures. I practically wrote down everything what he said. It helps also if you did not watch the weblecture, because you can find here everything what he talked about.
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- 8 december 2017
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